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A data replica placement strategy for IoT workflows in collaborative edge and cloud environments

机译:协作边缘和云环境中IoT工作流程的数据副本放置策略

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The convergence of edge and cloud computing shares their strengths, such as unlimited shared storage and computing resources from cloud, low-latency data preprocessing of edge computing. The collaboration of the two computing paradigms can provide a real-time and cost-effective way to deploy Internet of Things (loT) workflows among cooperative user groups. Since huge amounts of datasets continuously generated from user devices, how to place them to reduce the data access costs while meeting the deadline constraint is a critical issue. This paper proposed a novel data replica placement strategy for coordinated processing data-intensive loT workflows in collaborative edge and cloud computing environment. Firstly, data replica placement can be modelled as a 0-1 integer programming problem to consider the overall data dependency, data reliability and user cooperation. And then, the ITO algorithm, a variant of intelligent swarm optimization, is presented to address this model. The experimental results show that the proposed method outperforms these compared algorithms. It can not only find a higher quality solution of data replica placement, but also need a lower computing budget compared with these traditional algorithms. (C) 2018 Elsevier B.V. All rights reserved.
机译:边缘和云计算的融合共享其优势,例如无限共享的存储和来自云的计算资源,边缘计算的低延迟数据预处理。两种计算范例的协作可以提供一种实时且经济高效的方式来在合作用户组之间部署物联网(loT)工作流。由于从用户设备连续生成大量数据集,因此如何在满足截止期限约束的同时放置它们以减少数据访问成本是一个关键问题。本文提出了一种新的数据副本放置策略,用于在协作边缘和云计算环境中协调处理数据密集型loT工作流。首先,可以将数据副本的放置建模为0-1整数编程问题,以考虑整体数据依赖性,数据可靠性和用户合作。然后,提出了ITO算法,它是智能群优化的一种变体,用于解决该模型。实验结果表明,所提出的方法优于这些比较算法。与这些传统算法相比,它不仅可以找到高质量的数据副本放置解决方案,而且还需要较低的计算预算。 (C)2018 Elsevier B.V.保留所有权利。

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